Project acronym IndiviStat
Project Individualizing statin therapy by using a systems pharmacology decision support algorithm
Researcher (PI) Mikko Olavi NIEMI
Host Institution (HI) HELSINGIN YLIOPISTO
Call Details Consolidator Grant (CoG), LS7, ERC-2016-COG
Summary Background: Statins are essential drugs in the treatment of hypercholesterolaemia and are among the most prescribed drugs worldwide. The response to statin therapy varies widely between individuals. While most patients show good efficacy, a significant proportion of individuals show poor or even a lack of cholesterol-lowering efficacy. Moreover, a number of patients experience adverse drug reactions. These together with the lack of immediate effect on well-being likely explain the relatively poor adherence to statin therapy. Poor adherence to statins in turn increases the incidence of cardiovascular events and mortality.
Aims: The objectives of this project are 1) to develop a systems pharmacology model for predicting statin efficacy and tolerability at the level of an individual patient and 2) to investigate whether selecting the statin based on the model improves treatment adherence.
Methods: A systems pharmacology approach will be used to integrate data from in vitro and clinical studies. Semi-physiological pharmacokinetic-dynamic-toxicologic models will be built for each statin allowing the prediction of the pharmacokinetic and clinical outcomes for patients with different characteristics, genotypes, and concomitant medications. The ability of the systems pharmacology algorithm to enhance adherence will be investigated in a randomized clinical trial.
Significance: Systems pharmacology models have been increasingly applied in drug development, for example to predict the effect of organ dysfunction on pharmacokinetics. The proposed project is the first to use systems pharmacology predictions to guide clinical drug therapy, thus going beyond the state of the art. If successful, the project will not only improve the prevention and treatment of cardiovascular disease, but it will open new horizons to individualizing drug therapies.
Summary
Background: Statins are essential drugs in the treatment of hypercholesterolaemia and are among the most prescribed drugs worldwide. The response to statin therapy varies widely between individuals. While most patients show good efficacy, a significant proportion of individuals show poor or even a lack of cholesterol-lowering efficacy. Moreover, a number of patients experience adverse drug reactions. These together with the lack of immediate effect on well-being likely explain the relatively poor adherence to statin therapy. Poor adherence to statins in turn increases the incidence of cardiovascular events and mortality.
Aims: The objectives of this project are 1) to develop a systems pharmacology model for predicting statin efficacy and tolerability at the level of an individual patient and 2) to investigate whether selecting the statin based on the model improves treatment adherence.
Methods: A systems pharmacology approach will be used to integrate data from in vitro and clinical studies. Semi-physiological pharmacokinetic-dynamic-toxicologic models will be built for each statin allowing the prediction of the pharmacokinetic and clinical outcomes for patients with different characteristics, genotypes, and concomitant medications. The ability of the systems pharmacology algorithm to enhance adherence will be investigated in a randomized clinical trial.
Significance: Systems pharmacology models have been increasingly applied in drug development, for example to predict the effect of organ dysfunction on pharmacokinetics. The proposed project is the first to use systems pharmacology predictions to guide clinical drug therapy, thus going beyond the state of the art. If successful, the project will not only improve the prevention and treatment of cardiovascular disease, but it will open new horizons to individualizing drug therapies.
Max ERC Funding
2 211 565 €
Duration
Start date: 2017-08-01, End date: 2022-07-31
Project acronym PD UpReg
Project Gene knock-up via 3’UTR targeting to treat Parkinson’s disease
Researcher (PI) JAAN-OLLE ANDRESSOO
Host Institution (HI) HELSINGIN YLIOPISTO
Call Details Consolidator Grant (CoG), LS7, ERC-2016-COG
Summary Parkinson’s disease (PD) affects 1% of elderly persons and is currently incurable. PD pathogenesis is driven, at least in part, by defects in proteostasis and mitochondrial function, leading to degeneration of dopaminergic axons and neuronal death. Neurotrophic factors (NTFs) such as GDNF can protect and restore dopaminergic axons. However, attempts to deploy NTFs ectopically in therapy models, or to increase proteostasis and mitochondrial function, have met with only limited success.
I hypothesize that instead of ectopic application, over-expression of relevant pathways restricted to physiologically appropriate cells provides a potent therapeutic approach to treat PD. I have made significant progress toward this goal by targeting the 3’UTR in the mouse Gdnf gene, thereby increasing expression levels without affecting the gene’s spatiotemporal expression pattern. Using this approach I have shown that elevation of endogenous GDNF levels protects mice from experimentally induced PD. Unlike ectopic GDNF application, it causes no side effects. Importantly, I have established that GDNF levels can be elevated by 3’UTR targeting in adulthood, suggesting that this strategy could be applied in humans late in life.
I will use 3’UTR targeting to study the therapeutic potential of overexpressing endogenous genes, using transgenics and CRISPR-Cas9‒mediated 3’UTR editing in adult mice. First, I will increase the expression of NTFs in adult mice with experimentally induced PD. Next, I will upregulate genes important in mitochondrial function and proteostasis and test whether concurrently upregulating endogenous NTFs is a viable approach for treating PD. Third, I will use 3’UTR targeting to create a mouse model of PD in which alpha-synuclein is overexpressed, for better validation of my therapeutic strategy. Collectively, these experiments should establish proof of concept for a revolutionary, safe and effective treatment for PD.
Summary
Parkinson’s disease (PD) affects 1% of elderly persons and is currently incurable. PD pathogenesis is driven, at least in part, by defects in proteostasis and mitochondrial function, leading to degeneration of dopaminergic axons and neuronal death. Neurotrophic factors (NTFs) such as GDNF can protect and restore dopaminergic axons. However, attempts to deploy NTFs ectopically in therapy models, or to increase proteostasis and mitochondrial function, have met with only limited success.
I hypothesize that instead of ectopic application, over-expression of relevant pathways restricted to physiologically appropriate cells provides a potent therapeutic approach to treat PD. I have made significant progress toward this goal by targeting the 3’UTR in the mouse Gdnf gene, thereby increasing expression levels without affecting the gene’s spatiotemporal expression pattern. Using this approach I have shown that elevation of endogenous GDNF levels protects mice from experimentally induced PD. Unlike ectopic GDNF application, it causes no side effects. Importantly, I have established that GDNF levels can be elevated by 3’UTR targeting in adulthood, suggesting that this strategy could be applied in humans late in life.
I will use 3’UTR targeting to study the therapeutic potential of overexpressing endogenous genes, using transgenics and CRISPR-Cas9‒mediated 3’UTR editing in adult mice. First, I will increase the expression of NTFs in adult mice with experimentally induced PD. Next, I will upregulate genes important in mitochondrial function and proteostasis and test whether concurrently upregulating endogenous NTFs is a viable approach for treating PD. Third, I will use 3’UTR targeting to create a mouse model of PD in which alpha-synuclein is overexpressed, for better validation of my therapeutic strategy. Collectively, these experiments should establish proof of concept for a revolutionary, safe and effective treatment for PD.
Max ERC Funding
1 999 987 €
Duration
Start date: 2017-09-01, End date: 2022-08-31
